Mathematical finance in Rust
- Analytic
- Monte Carlo
- GBM
[*] local volatility
[*] stochastic local volatility
- risk figures
[*] Markovitz portofolio optimization
[*] Black Litterman
[*] Deep Hedging
[*] planned.
Any contribution and help is highly welcome! Work needs to be done in general and in particular
- further model implementations
- code and design improvements
- unit testing: correctness, regression, performance
- documentation, references, example implementations (and many more areas)
Run flamegraph for detecting hot paths. Running unit tests via this workaround
For example:
cargo b --tests --release
flamegraph target/release/deps/pricing-8329770a5e5551d4 -- test-name(e.g. no_drift_stock_price_simulation) [--output ./flamegraph/flamegraph.svg]
Find the flamegraph.svg and 'perf.data' at the project's root / flamegraph folder.
For benchmarking with criterion, run
cargo bench